The Global Optimization Algorithm: Newly Updated With Java Implementation And Parallelization (springerbriefs In Optimization)

This book explores the updated version of the GLOBAL algorithm which contains improvements for a local search algorithm and new Java implementations. Efficiency comparisons to earlier versions and on the increased speed achieved by the parallelization, are detailed. Examples are provided for students as well as researchers and practitioners in optimization, operations research, and mathematics to compose their own scripts with ease. A GLOBAL manual is presented in the appendix to assist new users with modules and test functions. GLOBAL is a successful stochastic multistart global optimization algorithm that has passed several computational tests, and is efficient and reliable for small to medium dimensional global optimization problems. The algorithm uses clustering to ensure efficiency and is modular in regard to the two local search methods it starts with, but it can also easily apply other local techniques. The strength of this algorithm lies in its reliability and adaptive algorithm parameters. The GLOBAL algorithm is free to download also in the earlier Fortran, C, and MATLAB implementations.-- Provided by publisher Contents......Page 3 1.1 Introduction......Page 6 1.3 The GLOBAL Algorithm......Page 7 2.1 Introduction......Page 11 2.2.1 Derivative-Free Local Search......Page 12 2.2.3 The New UNIRANDI Algorithm......Page 13 2.2.4 Reference Algorithms......Page 18 2.3.1 Experimental Settings......Page 19 2.3.2 Comparison of the Two UNIRANDI Versions......Page 20 2.3.3 Comparison with Other Algorithms......Page 22 2.3.4 Error Analysis......Page 23 2.3.5 Performance Profiles......Page 26 2.4 Conclusions......Page 29 3.1 Introduction......Page 30 3.3 Modularization......Page 31 3.4 Algorithmic Improvements......Page 34 3.5 Results......Page 40 3.6 Conclusions......Page 42 4.1 Introduction......Page 43 4.2.1 Principles of Parallel Computation......Page 44 4.3 Design of PGLOBAL Based on GLOBAL......Page 46 4.4.1 SerializedGlobal......Page 50 4.4.2 SerializedClusterizer......Page 53 4.7 Algorithm Parameters......Page 58 4.8.1 Environment......Page 59 4.8.2 SerializedGlobal Parallelization Test......Page 60 4.8.3 SerializedGlobalSingleLinkageClusterizer Parallelization Test......Page 63 4.8.4 Comparison of Global and PGlobal Implementations......Page 64 4.9 Conclusions......Page 68 5.2 Objective Function......Page 70 5.3 Optimizer Setup......Page 72 5.4 Run the Optimizer......Page 73 5.5 Constraints......Page 74 5.6 Custom Module Implementation......Page 78 A.1.1 Parameters......Page 81 A.2.1 Parameters......Page 82 A.3.1 Parameters......Page 83 A.5.1 Parameters......Page 84 A.7 UnirandiCLS Module......Page 85 A.8.1 Parameters......Page 86 A.10 LineSearchImpl Module......Page 87 Test Functions......Page 88 DiscreteClimber Code......Page 99 Refs......Page 105